Healthcare Analytics in a Disconnected World

Some of the most critical data required to solve analytical problems in the healthcare and life sciences world lack the type of keys that we rely on so heavily in other domains. This session will focus on solutions to the fundamental data connectivity challenges in this area and how to enable impactful analytics on a few high value but disconnected healthcare data sources.

The 10x growth of transaction volumes, 50x growth in data volumes and drive for real-time visibility and responsiveness over the last decade have pushed traditional technologies including databases beyond their limits. Your choices are either buy expensive hardware to accelerate the wrong architecture, or do what other companies have started to do and invest in technologies being used for modern hybrid transactional analytical applications (HTAP).

Learn some of the current best practices in building HTAP applications, and the differences between two of the more common technologies companies use: Apache® Cassandra™ and Apache® Ignite™. This session will cover:

- The requirements for real-time, high volume HTAP applications
- Architectural best practices, including how in-memory computing fits in and has eliminated tradeoffs between consistency, speed and scale
- A detailed comparison of Apache Ignite and GridGain® for HTAP applications

About the speaker: Denis Magda is the Director of Product Management at GridGain Systems, and Vice President of the Apache Ignite PMC. He is an expert in distributed systems and platforms who actively contributes to Apache Ignite and helps companies and individuals deploy it for mission-critical applications. You can be sure to come across Denis at conferences, workshop and other events sharing his knowledge about use case, best practices, and implementation tips and tricks on how to build efficient applications with in-memory data grids, distributed databases and in-memory computing platforms including Apache Ignite and GridGain.

Before joining GridGain and becoming a part of Apache Ignite community, Denis worked for Oracle where he led the Java ME Embedded Porting Team -- helping bring Java to IoT.

Attend this session to learn how to easily share state in-memory across multiple Spark jobs, either within the same application or between different Spark applications using an implementation of the Spark RDD abstraction provided in Apache Ignite. During the talk, attendees will learn in detail how IgniteRDD – an implementation of native Spark RDD and DataFrame APIs – shares the state of the RDD across other Spark jobs, applications and workers. Examples will show how IgniteRDD, with its advanced in-memory indexing capabilities, allows execution of SQL queries many times faster than native Spark RDDs or Data Frames.

Akmal Chaudhri has over 25 years experience in IT and has previously held roles as a developer, consultant, product strategist and technical trainer. He has worked for several blue-chip companies such as Reuters and IBM, and also the Big Data startups Hortonworks (Hadoop) and DataStax (Cassandra NoSQL Database). He holds a BSc (1st Class Hons.) in Computing and Information Systems, MSc in Business Systems Analysis and Design and a PhD in Computer Science. He is a Member of the British Computer Society (MBCS) and a Chartered IT Professional (CITP).

When monitoring an increasing number of machines, the infrastructure and tools need to be rethinked. A new tool, ExDeMon, for detecting anomalies and raising actions, has been developed to perform well on this growing infrastructure. Considerations of the development and implementation will be shared.

Daniel has been working at CERN for more than 3 years as Big Data developer, he has been implementing different tools for monitoring the computing infrastructure in the organisation.

As data analytics becomes more embedded within organizations, as an enterprise business practice, the methods and principles of agile processes must also be employed.

Agile includes DataOps, which refers to the tight coupling of data science model-building and model deployment. Agile can also refer to the rapid integration of new data sets into your big data environment for "zero-day" discovery, insights, and actionable intelligence.

The Data Lake is an advantageous approach to implementing an agile data environment, primarily because of its focus on "schema-on-read", thereby skipping the laborious, time-consuming, and fragile process of database modeling, refactoring, and re-indexing every time a new data set is ingested.

With new technologies such as Hive LLAP or Spark SQL, do you still need a data warehouse or can you just put everything in a data lake and report off of that? No! In the presentation, James will discuss why you still need a relational data warehouse and how to use a data lake and an RDBMS data warehouse to get the best of both worlds.

James will go into detail on the characteristics of a data lake and its benefits and why you still need data governance tasks in a data lake. He'll also discuss using Hadoop as the data lake, data virtualization, and the need for OLAP in a big data solution, and he will put it all together by showing common big data architectures.

Watson is a computer system capable of answering questions posed in natural language. Watson was named after IBM's first CEO, Thomas J. Watson. The computer system was specifically developed to answer questions on the quiz show Jeopardy! (where it beat its human competitors) and was then used in commercial applications, the first of which was helping with lung cancer treatment.

NetApp is now using IBM Watson in Elio, a virtual support assistant that responds to queries in natural language. Elio is built using Watson’s cognitive computing capabilities. These enable Elio to analyze unstructured data by using natural language processing to understand grammar and context, understand complex questions, and evaluate all possible meanings to determine what is being asked. Elio then reasons and identifies the best answers to questions with help from experts who monitor the quality of answers and continue to train Elio on more subjects.

Elio and Watson represent an innovative and novel use of large quantities of unstructured data to help solve problems, on average, four times faster than traditional methods. Join us at this webcast, where we’ll discuss:

AI is changing the way organizations do businesses and how they interact with customers. AI continues to drive the change. Deep Learning and Natural Language Processing will become standards in AI solutions. Deep Learning is based on brain simulations and uses deep neural networks. AlphaGo is the first AI system to defeat a professional human Go player, the first program to defeat a Go world champion, and arguably the strongest Go player in history. Baidu improved speech recognition from 89% to 99% using Deep Learning. Every AI and Machine learning scientist is required to know Deep Learning tools in his / her current job scenario.

In this session, we will be discussing what is Deep Learning and why it is gaining popularity. We will explain AI solutions using Deep Learning with a practical example. Deep Learning has an edge over other machine learning techniques as with the increased volume of data, performance increases with Deep Learning. Further, Deep Learning enables Hierarchical Feature Learning i.e. learning feature hierarchies.

In analytical reporting, often the data and presentation of it are perfect, but the data story falls flat. Looking to storytelling techniques from Hollywood, one can effectively drive home the point of their data and take their data visualizations to the next level.

Join Ted Frank, Principal at Backstories Studio for this webinar as he shows you the quick wins in storytelling, so right away, you can have your stakeholders understanding more and eager, on the edge of their seats. It starts with finding your key story and staying out of the weeds, then how to visualize it, and finally, how to deliver it so you get heard and make a bigger difference.

You can reach Ted at the following:
- ted@backstories.tv
- www.backstories.tv

Discover his book Get to the Heart below:
- ted@getotheheartbook.com
- www.gettotheheartbook.com

In this talk we will see whether we are building our first product or revamping an existing one, Embedded Analytics can help us solve real customer problems, which builds product value and creates a competitive differentiator to propel our business forward.

Additionally, we'll deeply look into how Embedded Analytics is different from Traditional Business Intelligence and what are the factors/trends driving Embedded Analytics.

Selling your house in the financial crisis-stricken Greece is up to this day a great ordeal. When faced with such a challenge, I was baffled by the sparsity of conclusive data on land value at my birthplace city, Thessaloniki. Embarking on a personal mission and collecting and processing more than 10K online housing ads together with open data, I managed to render an insightful interactive visualization of the actual real estate values on borough and city block level that was published through the Greek media. Join me on this thought process journey to find out how to

It can be hard to keep up with the rapidly changing BI landscape. But it doesn't have to be. Reserve your spot at Qlik's annual BI Trends Webinar.

In this global webinar live replay, we’ll reveal the top BI Trends for the coming year and how they can help you transform your data. Join Qlik’s Global Market Intelligence lead and former Gartner analyst Dan Sommer to learn why 2018 is the year for the “desilofication of data.”

Recent events like the Equifax data leak and new regulations like the EU's General Data Protection Regulation have increased the urgency for further change in the BI landscape and to move data out of silos.

What is the right strategy and framework?
How can you easily move from "all data," to "combinations of data," to "data insights"?
Can data literacy and augmented intelligence create a data-driven culture?
The volume of data available to decision makers continues to be massive, and is growing faster than our ability to consume it. Learn how to move your data out of silos and turn your data into insights.

RIDE supports developing in notebooks, editor, RMarkdown, shiny app, Bokeh and other frameworks. Supported by R-Brain’s optimized kernels, R and Python 3 have full language support, IntelliSense, debugger and data view. Autocomplete and content assistant are available for SQL and Python 2 kernels. Spark (standalone) and Tesnsorflow images are also provided.

Using Docker in managing workspaces, this platform provides an enhanced secure and stable development environment for users with a powerful admin control for controlling resources and level of access including memory usage, CPU usage, and Idle time.

The latest stable version of IDE is always available for all users without any need of upgrading or additional DevOps work. R-Brain also delivers customized development environment for organizations who are able to set up their own Docker registry to use their customized images.

The RIDE Platform is a turnkey solution that increases efficiency in your data science projects by enabling data science teams to work collaboratively without a need to switch between tools. Explore and visualize data, share analyses, all in one IDE with root access, connection to git repositories and databases.

Hear from our expert panel how they built a strong analytics culture in their organisations to enable data-driven decision-making.

We have invited Paul Banoub (UBS, United Kingdom), Emma Whyte (The Information Lab, United Kingdom), Simon Beaumont (NHS), and Josh Tapley (ComCast, United States) to discuss the following topics with us:
-How to find talented people and how to keep them engaged, challenged and motivated
-How to establish the right environment with processes and systems that foster innovation, learning, collaboration and analytical excellence
-How to setup best practices and governance while staying responsive to the organisation's need for information and insights RIGHT NOW
-How to make self-service analytics a success

During the panel discussion you have the chance to ask questions and get answers from our experts.

Presenters: Andy Kriebel, Head Coach at The Data School & Eva Murray, Head of BI and Tableau Evangelist at Exasol
Panel: Paul Banoub (Director, Analytics as a Service at UBS Investment Bank), Emma Whyte (Head of Centre of Excellence and Customer Advocacy at The Information Lab), Josh Tapley (Director, Data Visualization at Comcast)

IT is a key player in the digital and cognitive transformation of business processes delivering solutions for improved business value with analytics. This session will step by step explain the journey to secure production while adopting new analytics technologies leveraging mainframe core business assets

Unlocking the data’s true value is a challenge, but there are a range of tools and techniques that can help. This live discussion will focus on the data analytics landscape; compliance considerations and opportunities for improving data utility in 2018 and beyond.

Mixed reality is the result of blending the physical world with the digital world. Though it is relatively new technology and its adoption is still in initial stages. Mixed Reality devices and applications are projected to be the next technological era after smart phones.

The webinar will give a brief on Mixed Reality Potential Usecases those provide an immersive experience but also revenues streams to the creators.

Data Scientists are rare and highly valued individuals, and for good reason: making sense of data, and using the machine learning libraries requires an unusual blend of advanced skills. Why is it then that Data Scientists spend the majority of their time getting data ready for models, and a fraction actually doing the high value work?

In this talk we introduce the concept of Data Fabric, a new way to provide a self-service model for data, where data scientists can easily discover, curate, share, and accelerate data analysis using Python, R, and visualization tools, no matter where the data is managed, no matter the structure, and no matter the size.

We will talk through the role of Apache Arrow, the in-memory columnar data standard that is accelerating analytics for GPU-based processing, as well as the role of Pandas and Arrow in providing unprecedented speed in accessing datasets from Python.

Vivit launches their first ever SIG Talk event with three speakers who will give you insights into StormRunner Functional, Dynamic data handling in performance tests as well as AI and machine learning as it applies to testing.

We will discuss:

•How StormRunner Functional is the latest functional test offering from Micro Focus. In this session, Chris Trimper, an early adopter and beta tester, will share his experiences with this new product

•How Virtual Table Server (VTS), in days of Mercury Interactive, was the often-overlooked repository for dynamically updated real-time test data. Even after a revamp and relaunch in 2014, many people still don't use it, but they should. Richard's VTS demo will help you to get value from this great add-on for LoadRunner and Performance Center

•How Big Data, Artificial Intelligence and Machine learning are rapidly impacting businesses and customers, enabling another massive shift through technology enablement. In this session, Todd DeCapua will share how these capabilities are being leveraged in Performance Engineering now, and into the future

Join us for the next Quality & Testing SIG Talk on Tuesday, January 9, 2018: http://www.vivit-worldwide.org/events/EventDetails.aspx?id=1041157&group=.

Data is the foundation of any organization and therefore, it is paramount that it is managed and maintained as a valuable resource.

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